code: def plot_sandwich_data(x, y, axis=plt, colors="rbgmky"):
      for idx, val in enumerate(np.unique(y)):
          xi = x[y == val]
          axis.scatter(
              *xi.T, s=50, facecolors="none", edgecolors=colors[idx]
          )
  
file_path: metric-learn/examples/plot_sandwich.py
imports: import numpy
  from matplotlib import pyplot
  from sklearn.metrics import pairwise_distances
  from sklearn.neighbors import NearestNeighbors
  from metric_learn import LMNN, ITML_Supervised, LSML_Supervised, SDML_Supervised
label_desc: Use image node_id 5 for calling a global function with example usage: plot_sandwich_data(x, y, axis, colors) without return types